Furkan Kınlı #147 - He lå e loi la

Looking for the opportunities for Post-Doc or Visiting Researcher positions.

About Me

  • I received my Ph.D. (advised by Assoc. Prof. Furkan Kıraç), M.Sc., and B.Sc. degrees in Computer Science Department at Özyeğin University (YES, Triple crown!).

  • My research interests focus on image restoration, camera pipeline, illuminance and colors and computational photography.

  • Previously, I have worked on the downstream applications of computer vision, particularly using deep learning approaches, as well as the applications of generative modeling, image-to-image translation, fashion image understanding and capsule networks.

Recent News

Academic Services

  • Reviewer, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • Reviewer, Elsevier Digital Signal Processing
  • Reviewer, IEEE/CAA Journal of Automatica Sinica
  • Reviewer, Imaging Science Journal
  • Reviewer, Journal of Experimental & Theoretical Artificial Intelligence
  • Reviewer, the IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) (2025, 2024, 2023)
  • Reviewer, the International Conference on Computer Vision (ICCV) (2025, 2023)
  • Reviewer, the European Conference on Computer Vision (ECCV) (2024, 2022)
  • Reviewer, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (2025, 2024, 2023)
  • Reviewer, The 39th Annual AAAI Conference on Artificial Intelligence (AAAI) 2025
  • Reviewer, International Conference on Pattern Recognition (ICPR) 2024
  • Reviewer, New Trends in Image Restoration and Enhancement workshop and challenges on image and video processing at CVPR (NTIRE) (2024, 2023, 2022, 2021)
  • Reviewer, Advances in Image Manipulation workshop in conjunction with ECCV (AIM) (2024, 2022, 2020)
  • Reviewer, Resource Efficient Deep Learning for Computer Vision workshop at ICCV (RCV) (2023)
  • Reviewer, 30th IEEE Conference on Signal Processing and Communications Applications
  • Reviewer, ML Reproducibility Challenge 2022 Edition
  • Reviewer, ML Reproducibility Challenge 2021 Edition